Laurent Gautier escribi?: > Javier P?rez Florido wrote: >> Dear list, >> I have 3 questions about threestep (affyPLM) and expresso (AFFY) >> functions: >> >> 1. Which type of pm correction does threestep function perform? >> PMonly? >> 2. I would like to preprocess my microarray experiment using the >> following steps within the preprocessing method: GCRMA as >> background correction, INVARIANTSET as normalization, PMONLY as pm >> correction and TUKEY-BIWEIGHT (MAS) as summarization procedure. Is >> there any function which I can use to perform it? As far as I >> know, expresso hasn't got GCRMA as background correction and >> threestep function hasn't got INVARIANTSET as normalization >> procedure. Any tips? > > In GCRMA it seems that it is named a background adjustment rather than a > background correction, and therefore do not fit in the existing > framework. > > The following might(*) bring GCRMA to affy (*: not tested): > bg.correct.gcrma <- bg.adjust.gcrma > upDate.bgcorrect.methods(c(bgcorrect.methods(), "gcrma")) Thanks Prof. Gautier, it worked like you said. Now, I am able to use gcrma as background "method" in expresso. > > For threestep, the set of normalization methods it accepts is an > hard-coded list. Editing the code to make it accept an other method > at the R level is rather simple, but one should check what is happening > with those method names at the C level. > Going the other way around and write a summary method for affy that > performs the fit of a linear model of your choosing is also an > alternative. > > >> 3. If I want to perform MAS preprocessing using expresso, I think I >> should do it like this: >> >> eset<- expresso(data, bgcorrect.method = "mas", pmcorrect.method >> = "mas", normalize = FALSE, summary.method = "mas") >> eset<-affy.scalevalue.exprSet(eset) >> exprs(eset)<-log2(exprs(eset)) > > The source is open: > >> mas5 > function (object, normalize = TRUE, sc = 500, analysis = "absolute", > ...) > { > res <- expresso(object, bgcorrect.method = "mas", pmcorrect.method > = "mas", > normalize = FALSE, summary.method = "mas", ...) > if (normalize) > res <- affy.scalevalue.exprSet(res, sc = sc, analysis = analysis) > return(res) > } > <environment: namespace:affy=""> > > >> This is done this way because Affymetrix performs the normalization >> step after summarization. What about if I want to perform NO >> background correction, INVARIANTSET as normalization, MAS as pm >> correction and MAS as summarization? Is it like this? >> eset<- expresso(data, bgcorrect.method = "mas", pmcorrect.method >> = "mas", normalize.method="invariantset" summary.method = "mas") >> exprs(eset)<-log2(exprs(eset)) > > Most likely not. It looks like you copied/pasted the call to perform > MAS5.0 without a change. > The help pages contain how to get the method names. > Example: help("bgcorrect.methods") OK, you were right about mas5 method (Affy package) and I wrote the expresso command in the wrong way. What I wanted to mean is that Affymetrix performs the normalization step after summarization (I don`t know why). What I would like to know is if I want to use another normalization step than the one described for MAS (scaling), do I have to write the normalization step after the summarization? I mean, If I want to use "quantile" as normalization, I don't know if I have to proceed like this: res<- expresso(data, bgcorrect.method = "mas", pmcorrect.method = "mas", normalize = FALSE, summary.method = "mas") res2<-normalize(res,method="quantiles") exprs(res2)<-log2(exprs(res2)) or like this: res<- expresso(data, bgcorrect.method = "mas", pmcorrect.method = "mas", normalize.method = "quantiles", summary.method = "mas") exprs(res)<-log2(exprs(res)) Thanks again, Javier > > > L. > >> Thanks in advance, >> Javier >> >> >> [[alternative HTML version deleted]] >> >> _______________________________________________ >> Bioconductor mailing list >> Bioconductor at stat.math.ethz.ch >> https://stat.ethz.ch/mailman/listinfo/bioconductor >> Search the archives: >> http://news.gmane.org/gmane.science.biology.informatics.conductor > >